Risk Analysis in
Agricultural Policy
John D. McKenzie
Innovastat
5163 Independence Road
Boulder, CO 80301
Tel: (303) 516-1200
Fax: (303) 516-1202
john.mckenzie@innovastat.com
john.mckenzie@colorado.edu
john.mckenzie@darca.org
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Colorado
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Boulder
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McKenzie Farms
Since1893
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www.beyondorganicfarm.com
University of Colorado Student Run Farm
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Local Farmer
McClean County, Illinois
Richest Soil in the World
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InnovaAg
InnovaAg will help small farmers in Latin America &
Africa increase their productivity and incomes while
reducing risk through the use of decision and risk
technologies. The agricultural sectors in Latin America
& Africa have adopted technologies such as the
introduction of efficient irrigation systems and hybrid
seeds. However, one significant advancement that has
not been adequately implemented is the use of decision
making tools incorporating risk and uncertainty.
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Problem Statement
• Problems, in general, are easy to define and solve but
the dilemma arises in selling the solution. There is
resistance to changing the current paradigm of analysis
in the development field, Many development
professionals are not trained in quantitative risk and
decision analysis and may dismiss their use and
potential because they do not understand the concepts
even through they are widely used and proven in
industry and research. They are often reluctant to try
new and different ideas.
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The Problem (Where should you spend
your money in development work?)
The West has invested more then $2 trillion during the last 50
years on foreign aid to help the world’s poor.
What have been the results -what is there to show for it?
Many say not much.
A market failure? Antipoverty, global hunger, food
Why? - No accountability?
and income issues are
William Easterly, author speaks to
• Experts that plan
• Experts that search
public goods, as they are
not being provided in the
market place.
Farming systems are composed of highly complex biological
systems as well as the complex social interactions. These complex
systems require complex methods to analyze and solve problems.
12
World Food Problems
• Malthusian Problem
– Exponential growth of population
– Linear growth or no growth of resources or productivity
• Food Availability and Cost
– Food Crisis of 2007-2008 – riots all over the world,
high wheat and rice prices
– Mozambique, Sep 2010 – 30% increase in bread prices
riots leaving seven dead. Rising prices partly a result of
Russian ban on exports of their wheat. Can’t participate
in the market if your income is too low.
– Two edge sword – create opportunities for exports
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World Food Problems
• Chronic Hunger
– 925 million people will face chronic hunger this year
United Nations Food and Agriculture Organization (FAO)
• Hidden Hunger
– Two billion will suffer from hidden hunger, the lack
of vitamins and minerals that affects mental and
physical growth.
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Globalization and Food Security
• Growing incomes are putting pressure on commodity
prices and farm inputs.
– Growing meat consumption
– PotashCorp in Canada
• Global agricultural markets are volatile
– Core CPI does not include food and energy prices
– Rationale for subsidies in the U.S.
• Food Production will need to increase by 70% by
2050. (Sustainability and Security of the Global Food Supply Chain,
Rabobank Group 2010)
Millennium Development Goals
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Climate Change
• Farmers have noticed it.
• Weather changes, extreme events (recent floods in
Pakistan, rising temps.
• Colorado runoff has changed
• More impact in the developing world
– Sub-Sahara
• Need research in to increase productivity
including drought resistant varieties.
• Adaptive Strategies - $7 billion is needed in
improvements to offset climate changes calorie
reductions. IFPRI
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Problems of the Farmers
Farmers with limited resources require optimal
decisions so that they can feed their families and
avoid failure. A paradox exists – the corporate
world has resources for the use of sophisticated
decision-making technologies under uncertainty
while subsistence farmers do not. However, the
results of poor decision making at the farm level can
have a profound impact on the ability of farmers to
survive while corporate entities can more easily
survive incidents of poor judgment.
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What Are Your Options Or Consequences
In Cases of Bad Decisions?
• Stakes are higher than for large corporations for bad
decisions. Only choice may be to shut down.
• Farm resources can be limited – no deep pocket.
• “Layoffs” of resources is limited.
• Asset Specificity - inflexibility to switch resources.
• Decision making is more critical for farms and limited
resource companies than for large corporations.
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Problems of the Policy Makers
Policy makers, as well, have limited
resources. Unfortunately, most government
decision makers do not possess expertise in
sophisticated analytical techniques and view
farmer problems and their solutions as
simple and linear when in fact the
components of these farming systems are
more simultaneous, interdependent, and
involve varying levels of risk. These
decision makers often throw up their hands
and opt for a costly and inefficient back of
the envelope approach when these problems
seemingly become too complex.
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Bounded
Rationality In the
decision making process,
people speak of bounded
rationality according to
the work of Herbert
Simon. It states that
people have the inability
to process all the
alternatives of a problem.
That they can only look
at a half dozen solutions.
This is a cop out.
Overconfidence
in one’s abilities.
Is close enough
good enough? 20
Technology Adoption
Research and Development
The agricultural sectors in Latin America & Africa
have adopted technologies such as the introduction
of efficient irrigation systems and hybrid seeds.
However, one significant advancement that has
not been adequately implemented is the use of
decision making tools incorporating risk and
uncertainty.
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What Are These Decision
Making Technologies?
Descriptive
• Established Methods
– Accounting
– Enterprise Analysis
– Deterministic Optimization
Deterministic
• Ones That We Should Adopt
–
–
–
–
–
Monte Carlo Simulation
Simulation Optimization
Stochastic Optimization
Forecasting Under Uncertainty
Real Options
Analytical
Stochastic
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Decision Making Technologies
“Though at heart most business
problems are information problems,
almost no none is using information
well. But here on the edge of the
twenty-first century, the tools and
connectivity of the digital age now
give us a way to easily obtain, share,
and act on information in new and
remarkable ways.”
“…I work on planning under
uncertainty. That’s the big field
as far as I’m concerned; that’s the
future. Maybe I’m the only one
who says that. … all the
problems that are solved under
deterministic means have that
fundamental weakness- they don’t
properly take uncertainty into
account”
Business @ The Speed of Thought,
Bill Gates
George Dantzig – “Father of Linear
Programming”
OR/MS TODAY October 1999
See Appendix
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Analytics and Small Farms
• Sound decision analysis is critical for the success of
small farmers. We are all awash in huge amounts of
information and the problems and decisions facing
farmers are complex. Surprisingly, methods such as
Monte Carlo simulation and optimization under
uncertainty - employed routinely throughout the
corporate world - are not being applied to solve small
farmer problems. Without the benefit of these tools to
assess and manage risk, small farmers face conditions
that add significantly to their risk and reduce their
likelihood of success, sustainability and profitability.
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What are some of
the risks in Agriculture?
•
•
•
•
•
Production Risks
Market Risks
Financial Risks
Legal Risks
Human Resource Risks
Specialists advise farmers
on items such as what
crops to cultivate and
methods to use.
Nevertheless, these
suggestions are not based
or evaluated on local risk
conditions. As an
illustration, experts may
recommend purchasing
insurance but at what
price?
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What Do You Mean When You Say….
Qualitative Assessment
• “Planting winter wheat around here is more or less a sure thing
with very little risk?”
• The price of corn should be around $4.50 per bu. in September.
• “The water supply looks like it will be above average.”
• “If it snows and rains some more, then maybe river water will
be available. It would seem highly unlikely that we would get
no additional river water but it may be scant.”
May 2002 - Boulder and White Rock
Newsletter sent to shareholder.
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We Need To:
• Change gut feelings or
intuition about uncertain
events into:
– Probabilities that these
things will happen
expressed as a number
between 0 and 1.
• These probabilities can
be expressed
numerically.
– Analyses and different
scenarios can be
compared with these
numerical values.
• Odds = Probability of an Event
Occurring Divided by the
Probability of it not occurring.
• Odds = P/(1-P)
• Example:
– Probability of a stock
achieving at least a 15% return
is .66
– Then the odds are .66/(1-.66) =
2 or 2 to 1
– To convert back to probability
from odds
– 2/(2+1)
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Innovaag
InnovaAg will develop farm plans that include decisions that
minimize risk taking into account weather conditions,
commodity price fluctuations, input price changes, cultural
characteristics*, etc. These plans will give the farmer the greatest
chance of success (maximizing the certainty of achieving a
particular goal), and provide incomes that are greater and more
stable from season to season. Minimizing the fluctuations or
volatility in farm income will help the farmers avoid catastrophic
failure and allow them to remain on the land and continue
farming.
* Sociological inputs, e.g. being able to cooperate, chances of a
neighboring farmer being able to help in a timely manner. We use a
sociological indicator, the consumer confidence index in our
macroeconomic decision process.
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"Traditional assumptions about addressing poverty treat the
environment almost as an afterthought,…the stark reality of the poor:
three-fourths of them live in rural areas; their environment is all they can
depend on. Environmental resources are absolutely essential, rather
than incidental, if we are to have any hope of meeting our goals of
poverty reduction."
29
Jonathan Lash, president, World Resources Institute (WRI).
Growth Strategy For the Poor
• Based on the use of natural resources. These natural assets can be
the base of creating better conditions of poor people.
– Need to go from subsistence to participating in regional, national
and international economies
– Need to sustainably manage the resource base.
• World’s poor are in rural areas. Derive environmental income from
the natural resources.
• Environmental income:
– Wild Income (timber, medicinals, nature based tourism, carbon
storage payments)
– Agricultural Income
– Mineral and Energy Income
• Remember the physiocrats?
30
Community Benefits
Whole communities are the beneficiaries of the
output of the InnovaAg process. Greater incomes
will allow farmers to have more participation in
the marketplace and thus provide better for their
families in terms of housing, nutrition, health care,
and education for their children. The farmers
themselves, will decide how to best spend the
extra income that is generated, be it for family
expenditures or for farm improvements.
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Policy Makers
Beyond assisting individual small farmers, InnovaAg
will greatly enhance decision-making at the national
level. The results of the farmer input and the individual
farm plans will reveal the components of their systems
and will demonstrate that there are constraints that
thwart a successful outcome. When such constraints
are present, then relevant policy solutions by the
government need to be explored and implemented.
These policies can be in terms of research, education,
improved targeting and delivery of farm subsidies,
changes in laws, improvements in infrastructure or
credit, etc.
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An Illustration of Potential Solutions
Resulting from the Model Output
• Cell Phones
– Info on prices (information transfer makes free
markets work better)
– Getting buyers and sellers together.
– Technology transfer and adoption
• Kenya Farmers Helpline
– Financial services
• Cash transfers
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More Illustrations
•
•
•
•
•
Transnational cooperation
Railways, roads, storage, refrigeration
Waste reduction through the food chain.
Access to markets
You don’t know what
Diversification
appropriate solution to
implement unless you have
figured out what the problem is
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Process
InnovaAg is not imposing a top-down solution but
investigating and analyzing what currently exists at
the farm or community level in the context of risk.
Implementation of decision analysis tools first
involves learning and collecting information from
small farmers in the field and developing farm plans.
Training in applied risk analysis appropriate for small
farmers with little education will be offered. Tailormade plans will enable each farmer to decide the
optimal course of action based on his/her individual
goals and risk preferences.
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Process
The initial steps required would be to educate
funding agencies and government officials in the
field of risk and decision analysis through formal
training in the classroom and computer lab. They
need to be shown the usefulness so that there is a
chance that changes in the established ways of
decision-making can be elevated to a higher plateau.
Once they grasp the concept, they will find it
indispensible in their work. People may not believe in
an idea or process if they do
not understand it.
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Benefit/Cost
• The optimal outcome would be for these risk and
decision technologies to be accepted by the
development community and policy makers.
Although they are willing to promote technologies
such as better seeds and irrigation systems they
have, to date, been reluctant to adopt the many
tools of decision making. With adoption, the
money earmarked for development projects would
have a greater impact per dollar spent and a
benefit/cost analysis can be undertaken to
determine that effectiveness.
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Evaluation
The optimal outcome for farmers is a substantial
increase in their productivity, financial success,
and incomes and a significant decrease in the
volatility of these incomes from year to year. The
farmer results can be measured by receiving
feedback from the farmers and by evaluating preInnovaAg and post -InnovaAg incomes,
agricultural production, and farm improvements,
etc. Also, two similar groups, one with the
InnovaAg implementation and the other one
without can be statistically compared.
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Two Methods
• 40,000 feet above in the airplane
– Few assumptions that are generalized
• Outcome is more sensitive to assumptions
• 80/20 rule
• On the land with the farmers
– Decentralization of the decision process.
– The system is made up of more parts
– Less prone to overall misdirection.
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Case Study One
Continental Divide
Pacific
Atlantic
Inflows = f(Snow, rain, humidity, temp)
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Upper Colorado
River Basin
Missouri River Basin
Arkansas River Basin
Rio Grande
River Basin
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Upper Green
North Platte
White-Yampa Rivers
South Platte
Republican
Colorado Headwaters
Smokey Hill
Middle Arkansas
Gunnison
Upper Arkansas
Upper Colorado-Dolores
Rio Grande Headwaters
Lower San Juan
Upper San Juan
Upper Cimarron
Upper Rio Grande
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Case Study:
Surface
Creek
U
%
Surface Ck
U
%
U
%
U
%
U
%
U
%
U
%
U
%
U
%
See Appendix
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U
%
U
%
Locating, Mapping and Conducting Rehabilitation Assessment
2/10/05 to 8/24/07 (30 months)
Published and Distributed Reports to 14 Drainage Districts
Case Study Two
Las Animas
Lamar
Rocky Ford
La Junta
Lump all districts together or analyze
them separately?
Granada
Macro-analysis
– Macro-analysis (broad assumptions; x number of
dollars benefitted per acre, not dependent upon crop,
soil type, etc.) - typical benefit/cost analysis
aggregates all data, then applies a common model of
drainage enhancement for all the districts, and then
back out for the individual districts.
Micro-Analysis
• Micro-analysis (micro data analysis and assumptions)– build the benefit/cost
analysis incrementally, based on the rehabilitation of one district at a time, then
analyzing each subsequent district individually or in the aggregate.
– The more detailed the analysis, each individual part has less weight, and assumptions
that are off are not going to affect the output of the model as they would with a
model utilizing few global assumptions .
– The completed effort is the experimental group, while the uncompleted efforts are
the control group (s). What will the changes (reaction) in productivity and crop mix
be with the first rehabilitated district and what implications for future district
rehabilitation.
– Insightful, while at the same time being able to comparatively assess satisfaction and
performance of completed and uncompleted projects (i.e., adequate feedback).
– Determine the most effective order and scope of of rehabilitation and maximize the
cost effectiveness if funds are limited (i.e., portfolio analysis). For instance, is the
goal to maximize agricultural output, subject to a limitation on available funding?
Or, to maximize net income to farmers, subject a budget constraint?
FARM PLANNING UNDER UNCERTAINTY
YUMA COUNTY
• Sensitivity Analysis
• Monte Carlo Simulation
• Optimization Under
Uncertainty
Case Study Three
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The Future of Agriculture
• It is possible that the output of the model
will show that production agriculture is
not a sustainable activity in the long run.
• Farm in Yuma County, Colorado
– Without subsidies
– With subsidies
48
Maximize Profits
Crops To Grow
with Subsidies
Number of
Acres
Dryland Wheat
Irr Sugar Beets
Irr Alfalfa
Irr Dry Beans
1920
130
260
650
Without subsidies, the model tells us not to farm.
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PROYECTOS AGRÍCOLAS
BAJO INCERTIDUMBRE
Aldea de Tres Sábanas
50
Collect the data
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53
ENSAYO
RENDIMIENTO
PRECIO
GANANCIAS
1
$25.00
$2.50
$63
2
$24.00
$3.00
$72
3
$38.00
$3.50
$133
4
$38.00
$2.50
$95
5
$22.00
$3.00
$66
6
$33.00
$3.50
$116
7
$38.00
$3.50
$133
8
$38.00
$3.00
$114
9
$24.00
$2.50
$60
10
$25.00
$3.00
$75
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Back to Modeling -in the news
• Malawi – Disastrous harvest of 2005 resulted in
1/3 of population needing food aid– Since then
seed and fertilizer have been subsidized (despite
free market pleas from the World Bank, their
advice was to develop export cash crops to
develop an income stream) Result: the country
become a net food exporter in two years.
• Ghana – subsidies have helped increase food
production 40%
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Normality
• The distribution is an equation and this equation is trying to explain the
behavior of crop yields. Perhaps no equation can do that.
• The distribution relies on parameters for its input. A normal distribution
requires a mean and a standard deviation. The mean may not be an accurate
representation of the central point of the data. The mean is usually derived
from a sample and perhaps, more observations are required in order to
adequately describe the data and to limit the margin of error.
• When we summarize data into parameters like a mean and then further try to
force the data into an equation, accuracy is lost and the distribution may not
explain the real data adequately and truthfully.
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Histogram of Yields of Dryland Wheat in
Yuma County
1978-2007
8
The average
yield of 34.5
bushels occurs
3 times
7
6
4
3
2
1
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48.600
45.800
43.000
40.200
37.400
34.600
31.800
29.000
26.200
0
23.400
Frequency
5
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Frequency Distribution of Dryland Wheat Yields Overlay with
A Normally Distributed Yield Test of Normality
Yuma County 1978-2007
Chi-Square Test for Normality
8
7
Chi-Square Stat 7.37
P-value .3906
6
4
Bushels
Normal
3
2
1
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Bin # 10
Bin # 9
Bin # 8
Bin # 7
Bin # 6
Bin # 5
Bin # 4
Bin # 3
Bin # 2
0
Bin # 1
Bin Occupation
5
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Fitted Frequency Distribution for Dryland Wheat Yields
Yuma County 1978-2007
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The “average”
value of 45,010
acre feet doesn’t
occur very often.
The data appears non-normal (unlike a bell shaped curve) and bimodal (there are two humps to the curve)
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Water Supply Forecasting Using Nonparametric
Assumptions For the Holbrook Canal
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Traditional Approaches and Why They May
Not be Beneficial
• Single point estimates (averages do have a
margin of error)
• Sensitivity analysis or what if analysis.
• Scenario analysis
• Alternatives, Monte Carlo
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Monte Carlo Simulation
For Dryland Wheat
•
•
•
•
•
•
The model is the dryland wheat enterprise budget
We change two of the variables – yield and price
Add the correlations.
Add Decision Trees
Add Optimization
See Appendix
Add Forecasting
See CD
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Impediments That May Need Correction
Some endogenous, others exogenous
• Bad roads, lack infrastructure, corruption,
lack subsidies for factor inputs (fertilizer
and ag chemicals, lack of price floors, no
quotas, no tariffs, poor access to markets,
no cell phones, few tractors, poor
equipment, no irrigation systems, lack of
access to credit, poor varieties of seed,
intermittent electrical service…
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Correlations
•
•
A diversified economy is needed to
reduce risk – just like a farm – need
inputs that are not positively correlated.
The consequences of not
inputting the appropriate
correlation coefficients in
your model can lead you
astray.
Modern Portfolio Theory
– Models with less than
perfect correlation reduce
risk.
– Models with much
negative correlation
reduces your exposure to
risk
Var(A+B) = Var(A) + Var(B) +2Cov(A,B)
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Portfolios, Portfolios, Portfolios
Portfolios are commonly viewed as a group of individual
financial investments. Nevertheless, the definition of portfolio
can be extended to include a collection of various other
investments or courses of action that you may undertake.
Fortunately, with Monte Carl simulation and optimizer
software, “simple” models can generate sophisticated and
intuitive results.
You can use concepts of modern portfolio theory to solve your
specific models outside the realm of traditional models.
69
Portfolios
•
•
You can gain an appreciation of optimization under
uncertainty in the context of portfolios.
We can explore the features of @RISK Optimizer for
various portfolio optimizations. .
• Portfolio of stocks
• Portfolio of projects
• Portfolio of an oil field
• Portfolio of pharmaceuticals
• Portfolio of farms
70
Benefits of Stochastic Optimization or
Optimization Under Uncertainty
The ability to solve problems w/o calculus.
The ability to solve problem that traditional methods cannot accomplish. We
assume the normality of functions when in fact a better choice of words would be
“we pretend.”
Calculus was invented by
Leibnitz and Newton in
the late 1600s
Calculus requires a
continuous and
differentiable functions
71
Synergy
• The interaction of two
or more agents or
forces so that their
combined effect is
greater than the sum of
their individual effects.
"Synergy means behavior of whole systems unpredicted
by the behavior of their parts."
- R. [Richard] Buckminster Fuller (1895 - 1983)
72
Optimization Under Uncertainty
epiphany
3 a (1) : a usually sudden manifestation
or perception of the essential nature or
meaning of something (2) : an intuitive
grasp of reality through something (as
an event) usually simple and striking (3)
: an illuminating discovery
Principles of Parsimony and Simplicity
Occam’s Razor
“Many branches of pure and applied mathematics are in great need of computing
instruments to break the present stalemate created by the failure of the purely analytical
approach to nonlinear problems” (John von Neumann)
73
Optimization Under Uncertainty
• Maximize food security.
• Maximize the certainty of a certain return. (Some
farmers are risk averse and some may be risk
loving) (Can be non-parametric)
• Minimize the risk of a certain return.
You constraint
• Maximize the return for a given risk.
would contain a
• Other goals:
budget constraint.
– Minimize carbon footprint
– Minimize energy use
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Propuesta que no era financiado
DEVELOPING A MARKETING AND TRADING
CAPACITY OF FOREST PRODUCTS FOR INDIGENOUS AND
AFRO-COLOMBIANS IN THE
SOUTH PACIFIC COAST REGION OF COLOMBIA
Corporación Nacional de Investigación y Fomento Forestal
75
76
77
Constitution of 1991 provides collective
rights for lands of Indigenous and AfroColombians in their traditional communities.
78
"Traditional assumptions about addressing poverty treat the
environment almost as an afterthought,…the stark reality of the poor:
three-fourths of them live in rural areas; their environment is all they can
depend on. Environmental resources are absolutely essential, rather
than incidental, if we are to have any hope of meeting our goals of
poverty reduction."
79
Jonathan Lash, president, World Resources Institute (WRI).
Growth Strategy For the Poor
• Based on the use of natural resources. These natural assets can be
the base of creating better conditions of poor people.
– Need to go from subsistence to participating in regional, national
and international economies
– Need to sustainably manage the resource base.
• World’s poor are in rural areas. Derive environmental income from
the natural resources.
• Environmental income:
– Wild Income (timber, medicinals, nature based tourism, carbon
storage payments)
– Agricultural Income
– Mineral and Energy Income
• Remember the physiocrats?
80
Research and Risk Component
The research will provide the tools necessary so that the Trading
Company can make better decisions for their members through identification
of risk an mitigation strategies. Although considerable work has been
accomplished, there still is a lack of information about these specialized
forest product markets and there is a great need to gather data directly from
land holders and local sources along with regional, national and
international sources. Reliable data on these local forestry operations are
needed to develop an applied forestry portfolio model that will increase
the likelihood of communities developing and implementing a successful
whole forestry marketing plan under the known conditions of uncertainty that
they face.
Insight provided by the individual communities and their particular
circumstances will be one of the cornerstones of the project. Producer
workshops will be held to solicit feedback from the participants about their
operations in the context of risk and decision analysis. This activity is
designed to establish quantifiable measures for the whole forestry marketing
plans, as well to secure a feeling of producer ownership in the methods and
81
the Trading Company.
This information about their specific locale and their individual operation
risks will be inputted into models by the team members of the project. They
will be able to determine optimal courses of action based on the techniques
of Monte Carlo simulation, optimization under uncertainty, econometric
forecasting, and real options.
The marketing plan for the wood products can be viewed as a portfolio of
decisions. The Trading Company will be able to determine an optimal course
of action based on identified risk constraints. That is, what courses of action,
(e.g. selection of species, harvesting considerations, whether to export or sell
to the domestic market, terms, transportation considerations, insurance, input
decisions, etc.) would minimize the risk of achieving some expected minimum
level of profit. This expected level of profit may be one that would provide an
adequate standard of living for the Trading Company’s members.
The output of the models will allow the members of the Trading Company
to see the impact of the uncertain variables on their forecasted answer. A
sensitivity analysis will reveal to what degree those inputs into the model
affect the expected outcome. Knowing this information is extremely
informative; the trading company can concentrate on managing or controlling
the risk for this variable. Furthermore, the Colombian government might need
to initiate a change in this policy in order to control for this variable.
82
Risk Analysis in
Agricultural Policy
John D. McKenzie
Innovastat
5163 Independence Road
Boulder, CO 80301
Thanks for
attending!
Tel: (303) 516-1200
Fax: (303) 516-1202
john.mckenzie@innovastat.com
john.mckenzie@colorado.edu
john.mckenzie@darca.org
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83